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20222025
most citedData-Driven Sensor Selection Method Based on Proximal Optimization for High-Dimensional Data With Correlated Measurement Noise

29 citations · 156 across the 9 of their papers we have counts for

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5 papers · 1 filter

eess.SP2024★ 5 cited

Fast Data-driven Greedy Sensor Selection for Ridge Regression

Yasuo Sasaki, Keigo Yamada, Takayuki Nagata +2

We propose a data-driven sensor-selection algorithm for accurate estimation of the target variables from the selected measurements. The target variables are assumed to be estimated…

eess.SP2022★ 6 cited

Observation Site Selection for Physical Model Parameter Estimation toward Process-Driven Seismic Wavefield Reconstruction

Kumi Nakai, Takayuki Nagata, Keigo Yamada +5

The ``big'' seismic data not only acquired by seismometers but also acquired by vibrometers installed in buildings and infrastructure and accelerometers installed in smartphones wi…

eess.SP2022★ 29 cited

Data-Driven Sensor Selection Method Based on Proximal Optimization for High-Dimensional Data With Correlated Measurement Noise

Takayuki Nagata, Keigo Yamada, Taku Nonomura +3

The present paper proposes a data-driven sensor selection method for a high-dimensional nondynamical system with strongly correlated measurement noise. The proposed method is based…

eess.SP2022★ 19 cited

Randomized Group-Greedy Method for Large-Scale Sensor Selection Problems

Takayuki Nagata, Keigo Yamada, Kumi Nakai +2

The randomized group-greedy method and its customized method for large-scale sensor selection problems are proposed. The randomized greedy sensor selection algorithm is applied str…

eess.SP2022★ 26 cited

Nondominated-Solution-based Multi-objective Greedy Sensor Selection for Optimal Design of Experiments

Kumi Nakai, Yasuo Sasaki, Takayuki Nagata +3

In this study, a nondominated-solution-based multi-objective greedy method is proposed and applied to a sensor selection problem based on the multiple indices of the optimal design…